We present VOSviewer, a freely available computer program that we have developed for constructing and viewing bibliometric maps. Unlike most computer programs that are used for bibliometric mapping, VOSviewer pays special attention to the graphical representation of bibliometric maps. The functionality of VOSviewer is especially useful for displaying large bibliometric maps in an easy-to-interpret way. The paper consists of three parts. In the first part, an overview of VOSviewer’s functionality for displaying bibliometric maps is provided. In the second part, the technical implementation of specific parts of the program is discussed. Finally, in the third part, VOSviewer’s ability to handle large maps is demonstrated by using the program to construct and display a co-citation map of 5,000 major scientific journals.

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Software survey: VOSviewer, a computer program for bibliometric mapping.

Social Network Analysis

This chapter provides an introduction to the topic of visualizing bibliometric networks. First, the most commonly studied types of bibliometric networks (i.e., citation, co-citation, bibliographic coupling, keyword co-occurrence, and coauthorship networks) are discussed, and three popular visualization approaches (i.e., distance-based, graph-based, and timeline-based approaches) are distinguished. Next, an overview is given of a number of software tools that can be used for visualizing bibliometric networks. In the second part of the chapter, the focus is specifically on two software tools: VOSviewer and CitNetExplorer. The techniques used by these tools to construct, analyze, and visualize bibliometric networks are discussed. In addition, tutorials are offered that demonstrate in a step-by-step manner how both tools can be used. Finally, the chapter concludes with a discussion of the limitations and the proper use of bibliometric network visualizations and with a summary of some ongoing and future developments.

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Visualizing Bibliometric Networks

A review of the literature on citation impact indicators

This paper presents a new map representing the structure of all of science, based on journal articles, including both the natural and social sciences. Similar to cartographic maps of our world, the map of science provides a bird's eye view of today's scientific landscape. It can be used to visually identify major areas of science, their size, similarity, and interconnectedness. In order to be useful, the map needs to be accurate on a local and on a global scale. While our recent work has focused on the former aspect, this paper summarizes results on how to achieve structural accuracy. Eight alternative measures of journal similarity were applied to a data set of 7,121 journals covering over 1 million documents in the combined Science Citation and Social Science Citation Indexes. For each journal similarity measure we generated two-dimensional spatial layouts using the force-directed graph layout tool, VxOrd. Next, mutual information values were calculated for each graph at different clustering levels to give a measure of structural accuracy for each map. The best co-citation and inter-citation maps according to local and structural accuracy were selected and are presented and characterized. These two maps are compared to establish robustness. The inter-citation map is more » then used to examine linkages between disciplines. Biochemistry appears as the most interdisciplinary discipline in science. « less

Mapping the backbone of science.

Background: The impact of scientific publications has traditionally been expressed in terms of citation counts. However, scientific activity has moved online over the past decade. To better capture scientific impact in the digital era, a variety of new impact measures has been proposed on the basis of social network analysis and usage log data. Here we investigate how these new measures relate to each other, and how accurately and completely they express scientific impact. Methodology: We performed a principal component analysis of the rankings produced by 39 existing and proposed measures of scholarly impact that were calculated on the basis of both citation and usage log data. Conclusions: Our results indicate that the notion of scientific impact is a multi-dimensional construct that can not be adequately measured by any single indicator, although some measures are more suitable than others. The commonly used citation Impact Factor is not positioned at the core of this construct, but at its periphery, and should thus be used with caution.

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A principal component analysis of 39 scientific impact measures.

Background: Intricate maps of science have been created from citation data to visualize the structure of scientific activity. However, most scientific publications are now accessed online. Scholarly web portals record detailed log data at a scale that exceeds the number of all existing citations combined. Such log data is recorded immediately upon publication and keeps track of the sequences of user requests (clickstreams) that are issued by a variety of users across many different domains. Given these advantages of log datasets over citation data, we investigate whether they can produce high-resolution, more current maps of science. Methodology: Over the course of 2007 and 2008, we collected nearly 1 billion user interactions recorded by the scholarly web portals of some of the most significant publishers, aggregators and institutional consortia. The resulting reference data set covers a significant part of world-wide use of scholarly web portals in 2006, and provides a balanced coverage of the humanities, social sciences, and natural sciences. A journal clickstream model, i.e. a first-order Markov chain, was extracted from the sequences of user interactions in the logs. The clickstream model was validated by comparing it to the Getty Research Institute’s Architecture and Art Thesaurus. The resulting model was visualized as a journal network that outlines the relationships between various scientific domains and clarifies the connection of the social sciences and humanities to the natural sciences. Conclusions: Maps of science resulting from large-scale clickstream data provide a detailed, contemporary view of scientific activity and correct the underrepresentation of the social sciences and humanities that is commonly found in citation data.

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Clickstream Data Yields High-Resolution Maps of Science

The need to federate repositories emerges in two distinctive scenarios. In one scenario, scalability-related problems in the operation of a repository reach a point beyond which continued service requires parallelization and hence federation of the repository infrastructure. In the other scenario, multiple distributed repositories manage collections of interest to certain communities or applications, and federation is an approach to present a unified perspective across these repositories. The high-level, 3-Tier aDORe federation architecture can be used as a guideline to federate repositories in both cases. This paper describes the architecture, consisting of core interfaces for federated repositories in Tier-1, two shared infrastructure components in Tier-2, and a single-point of access to the federation in Tier-3. The paper also illustrates two large-scale deployments of the aDORe federation architecture: the aDORe Archive repository (over 100,000,000 digital objects) at the Los Alamos National Laboratory and the Ghent University Image Repository federation (multiple terabytes of image files).

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The aDORe federation architecture: digital repositories at scale

The ISO-standardized JPEG 2000 image format has started to attract significant attention. Support for the format is emerging in major consumer applications, and the cultural heritage community seriously considers it a viable format for digital preservation. So far, only commercial image servers with JPEG 2000 support have been available. They come with significant license fees and typically provide the customers with limited extensibility capabilities. Here, we introduce djatoka, an open source JPEG 2000 image server with an attractive basic feature set, and extensibility under control of the community of implementers. We describe djatoka, and point at demonstrations that feature digitized images of marvelous historical manuscripts from the collections of the British Library and the University of Ghent. We also caIl upon the community to engage in further development of djatoka.

Introducing djatoka: A Reuse Friendly, Open Source JPEG 2000 Image Server

This poster presents the architecture and user interface of a prototype service that was designed to allow end-users to explore the structure of science and perform assessments of scholarly impact on the basis of large-scale usage data. The underlying usage data set was constructed by the MESUR project which collected 1 billion usage events from a wide range of publishers, aggregators, and institutional consortia.

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Ryan Chute

Papers

A principal component analysis of 39 scientific impact measures.

Clickstream Data Yields High-Resolution Maps of Science

The aDORe federation architecture: digital repositories at scale

Introducing djatoka: A Reuse Friendly, Open Source JPEG 2000 Image Server

A ranking and exploration service based on large-scale usage data.